The rapid adoption of the Internet of Things (IoT) across various industries has significantly enhanced productivity and efficiency. However, the widespread deployment of battery-powered IoT devices raises concerns about energy sustainability, battery longevity, and environmental impact. Frequent battery replacements pose logistical challenges, particularly in large-scale networks and remote locations. To address these issues, the Green IoT (G-IoT) design framework has been introduced, emphasizing energy-efficient strategies such as duty cycling, transceiver optimization, energy-aware routing, and the integration of renewable energy sources like photovoltaic (PV) energy harvesting. Despite advancements in G-IoT, a major challenge remains: the dynamic and unpredictable nature of both IoT energy consumption and harvested energy. In this paper, we propose a design framework for Green IoT that models the interplay between energy harvesting, storage, and consumption processes. By incorporating time-varying energy dynamics, the proposed framework enables efficient dimensioning of energy harvesters and storage systems, ensuring optimal energy management in IoT networks. This approach allows for the evaluation of various energy-saving strategies and enhances the long-term sustainability of IoT deployments. Numerical examples and simulation results demonstrate the effectiveness of the framework in maintaining energy balance and extending the operational lifetime of IoT nodes.